Online Appendices ”WFH Productivity in Open-Source Projects” Lucas Shen (March 2021)

Figure A1: Largest countries in sample Notes. Sample size by country, in descending order. Panel (a) sorts countries by number of commits per user-repository. Panel (b) sorts countries by number of user-repository.

1 Figure A2: US states (by Commits) Notes. US sample size by states, in descending order. States sorted by number of commits per user-repository.

Figure A3: US states (by Users & Repositories) Notes. US sample size by states, in descending order. States sorted by number user-repository.

2 (a) Staggered Timing in County-level Business Closures

(b) County-level Variation in Sample Sizes Figure A4: Geographical Variation in US sample Notes—Panel (a) plots the county-level variation in business closures from the US-state level records and crowdsourced county-level records. Blue indicates earlier closures, while red indicates later closures. South Dakota is (still) the sole state without closure at the time of writing. Panel (b) plots the geographic variation of commits from geocoded U.S. users—larger markers indicate larger activity in the sample period.

3 (a) Early response (by 15 Feb)

(b) Intermediate response (by 17 Mar)

(c) Late response (by 30 Apr) Figure A5: Country variation in WFH enforcement Notes. Figure plots the variation in government-enforced WFH levels during the COVID-19 pandemic. WFH indicators come from the OxCGRT (?).

4 (a) Early response (by 15 Feb)

(b) Intermediate response (by 17 Mar) (c) Late response (by 30 Apr) Figure A6: U.S. states variation in WFH enforcement Notes. Figure plots the U.S. states variation in government-enforced WFH levels during the COVID-19 pandemic. WFH indicators come from the OxCGRT (?).

5 (a) Baseline (WFH = 0)

(b) Recommended WFH (WFH = 1)

(c) Required WFH for some (WFH = 2)

(d) Required WFH for all but essential (WFH = 3) Figure A7: Country variation in activity, by WFH status Notes. Figure plots the variation in activity level according to government-enforced WFH levels during the COVID-19 pandemic. These are from the commits per user-repo-day (for each given WFH period, total commits in that period divided by days in WFH period), aggregated up to the country-WFH level. Shaded areas indicate countries that do not have a particular WFH enforcement from Jan–Jun 2020. WFH indicators come from the OxCGRT (?).

6 (a) Baseline (WFH = 0) (b) Recommended WFH (WFH = 1)

(c) Required WFH for some (WFH = 2) (d) Required WFH for all but some (WFH = 3) Figure A8: U.S. states variation in activity, by WFH status Notes. Figure plots the variation in activity level according to U.S. state-level government-enforced WFH levels during the COVID-19 pandemic. These are from the commits per user-repo-day (for each given WFH period, total commits in that period divided bydaysinWFH period), aggregated up to the state-WFH level. Shaded areas indicate state that do not have a particular WFH enforcement from Jan–Jun 2020. WFH indicators come from the OxCGRT (?).

7 Table A1—Language Distribution (Commits sample)

language No. % JavaScript 16,392 16.98 Python 13,200 13.68 Java 9,712 10.06 PHP 6,884 7.13 Go 5,952 6.17 C++ 5,748 5.96 HTML 5,024 5.21 Ruby 4,128 4.28 TypeScript 3,588 3.72 C 3,516 3.64 Shell 3,224 3.34 CSS 2,972 3.08 C# 2,928 3.03 Scala 1,004 1.04 Jupyter Notebook 872 0.90 Rust 872 0.90 Swift 840 0.87 R 640 0.66 Vim script 620 0.64 Objective-C 596 0.62 Kotlin 536 0.56 Emacs Lisp 508 0.53 Perl 396 0.41 Dockerfile 392 0.41 Lua 376 0.39 Groovy 288 0.30 Clojure 272 0.28 Dart 272 0.28 PowerShell 272 0.28 MATLAB 260 0.27 TeX 248 0.26 Vue 248 0.26 Haskell 200 0.21 CoffeeScript 196 0.20 Erlang 184 0.19 Fortran 172 0.18 Elixir 168 0.17 TSQL 144 0.15 Julia 132 0.14 OCaml 116 0.12 Pascal 116 0.12 Assembly 108 0.11 Makefile 108 0.11 CMake 84 0.09 Visual Basic .NET 80 0.08 Starlark 76 0.08 Batchfile 72 0.07 F# 64 0.07 Nim 64 0.07 Vala 60 0.06 Smalltalk 56 0.06 ABAP 52 0.05 DM 52 0.05 Haxe 52 0.05 Crystal 48 0.05 PLpgSQL 48 0.05 Zig 48 0.05 D 40 0.04 Puppet 40 0.04 QML 40 0.04 XSLT 40 0.04 Common Lisp 36 0.04 Scheme 36 0.04 Vim Snippet 36 0.04 HCL 32 0.03 Jsonnet 32 0.03 VHDL 32 0.03 Elm 28 0.03 Roff 28 0.03 Continued on next page

8 Table A1 – Continued from previous page Language No. % Smarty 28 0.03 ActionScript 24 0.02 Ada 24 0.02 AutoHotkey 24 0.02 SourcePawn 24 0.02 Coq 20 0.02 Nix 20 0.02 Raku 20 0.02 Rich Text Format 20 0.02 SuperCollider 20 0.02 Markdown 16 0.02 OpenSCAD 16 0.02 PLSQL 16 0.02 Racket 16 0.02 Reason 16 0.02 Tcl 16 0.02 Verilog 16 0.02 ASP 12 0.01 BitBake 12 0.01 GLSL 12 0.01 Gherkin 12 0.01 IDL 12 0.01 Lasso 12 0.01 Mathematica 12 0.01 OpenEdge ABL 12 0.01 PureScript 12 0.01 RobotFramework 12 0.01 SQLPL 12 0.01 Stan 12 0.01 SystemVerilog 12 0.01 Apex 8 0.01 Cirru 8 0.01 ColdFusion 8 0.01 Cuda 8 0.01 HLSL 8 0.01 Hack 8 0.01 Isabelle 8 0.01 LiveScript 8 0.01 Logos 8 0.01 MQL5 8 0.01 MTML 8 0.01 Max 8 0.01 Objective-J 8 0.01 PostScript 8 0.01 Prolog 8 0.01 SWIG 8 0.01 Squirrel 8 0.01 YARA 8 0.01 YASnippet 8 0.01 sed 8 0.01 API Blueprint 4 0.00 AngelScript 4 0.00 ApacheConf 4 0.00 E 4 0.00 Factor 4 0.00 Forth 4 0.00 FreeMarker 4 0.00 G-code 4 0.00 GAMS 4 0.00 GAP 4 0.00 GDScript 4 0.00 Gnuplot 4 0.00 IGOR Pro 4 0.00 KiCad Layout 4 0.00 LLVM 4 0.00 LOLCODE 4 0.00 LabVIEW 4 0.00 Lex 4 0.00 Limbo 4 0.00 Continued on next page

9 Table A1 – Continued from previous page Language No. % M 4 0.00 Modelica 4 0.00 Modula-2 4 0.00 NewLisp 4 0.00 Nextflow 4 0.00 Objective-C++ 4 0.00 P4 4 0.00 Pawn 4 0.00 Pony 4 0.00 Processing 4 0.00 PureBasic 4 0.00 Rebol 4 0.00 Riot 4 0.00 SMT 4 0.00 SQF 4 0.00 VBA 4 0.00 VBScript 4 0.00 VimL 4 0.00 Volt 4 0.00 XProc 4 0.00 ZenScript 4 0.00 q 4 0.00 Total 96,516 100.00

10 Table A2—Language Distribution (Pull request sample)

Language No. % JavaScript 78,005 16.906 Python 72,598 15.734 PHP 36,556 7.923 Java 34,708 7.522 Go 33,132 7.181 Ruby 32,736 7.095 C++ 21,104 4.574 TypeScript 19,395 4.203 C 15,636 3.389 C# 13,724 2.974 Shell 13,592 2.946 HTML 12,640 2.739 Rust 7,284 1.579 Swift 7,172 1.554 CSS 6,748 1.462 Scala 4,940 1.071 Kotlin 3,264 0.707 Objective-C 3,076 0.667 Elixir 2,816 0.610 Jupyter Notebook 2,756 0.597 Haskell 2,656 0.576 Dart 2,220 0.481 Julia 2,136 0.463 Dockerfile 2,104 0.456 Emacs Lisp 1,916 0.415 Perl 1,668 0.362 Vim script 1,616 0.350 Groovy 1,596 0.346 Clojure 1,592 0.345 Lua 1,284 0.278 PowerShell 1,248 0.270 Erlang 1,240 0.269 R 1,232 0.267 CoffeeScript 964 0.209 OCaml 920 0.199 Vue 916 0.199 Makefile 852 0.185 Starlark 740 0.160 Crystal 672 0.146 PureScript 628 0.136 F# 588 0.127 Puppet 580 0.126 TSQL 472 0.102 TeX 460 0.100 CMake 456 0.099 Jsonnet 420 0.091 Vala 400 0.087 MATLAB 368 0.080 BitBake 336 0.073 Common Lisp 336 0.073 Smalltalk 316 0.068 Fortran 292 0.063 Haxe 288 0.062 HCL 272 0.059 Nim 268 0.058 Nix 248 0.054 PLpgSQL 244 0.053 Elm 236 0.051 Smarty 232 0.050 Assembly 204 0.044 XSLT 176 0.038 Gherkin 164 0.036 D 160 0.035 Raku 160 0.035 Roff 148 0.032 Pascal 136 0.029 Reason 120 0.026 Rich Text Format 116 0.025 SourcePawn 104 0.023 Continued on next page

11 Table A2 – Continued from previous page Language No. % Apex 100 0.022 ColdFusion 96 0.021 Scheme 96 0.021 Visual Basic .NET 96 0.021 ABAP 80 0.017 QML 80 0.017 Batchfile 76 0.016 Tcl 72 0.016 Coq 68 0.015 Objective-C++ 68 0.015 GDScript 64 0.014 Common Workflow Language 60 0.013 Cuda 60 0.013 Racket 60 0.013 VHDL 60 0.013 Prolog 56 0.012 SWIG 52 0.011 Agda 48 0.010 SaltStack 48 0.010 Vim Snippet 48 0.010 Zig 48 0.010 1C Enterprise 44 0.010 F* 44 0.010 Pawn 44 0.010 YASnippet 44 0.010 Lasso 40 0.009 Markdown 40 0.009 Perl 6 40 0.009 PLSQL 36 0.008 SystemVerilog 36 0.008 GAP 32 0.007 GLSL 32 0.007 Hack 32 0.007 IDL 32 0.007 M4 32 0.007 RobotFramework 32 0.007 SQF 32 0.007 Mathematica 28 0.006 Ada 24 0.005 Augeas 24 0.005 SuperCollider 24 0.005 Verilog 24 0.005 WebAssembly 24 0.005 q 24 0.005 AutoHotkey 20 0.004 Awk 20 0.004 FreeMarker 20 0.004 LookML 20 0.004 Nextflow 20 0.004 PostScript 20 0.004 Stan 20 0.004 VBA 20 0.004 YAML 20 0.004 YARA 20 0.004 Yacc 20 0.004 ANTLR 16 0.003 API Blueprint 16 0.003 Cirru 16 0.003 Dhall 16 0.003 Factor 16 0.003 OpenEdge ABL 16 0.003 P4 16 0.003 Pony 16 0.003 SQLPL 16 0.003 Visual Basic 16 0.003 Xtend 16 0.003 AutoIt 12 0.003 DIGITAL Command Language 12 0.003 DM 12 0.003 Continued on next page

12 Table A2 – Continued from previous page Language No. % Gnuplot 12 0.003 LilyPond 12 0.003 Logos 12 0.003 Stata 12 0.003 VimL 12 0.003 ASP 8 0.002 ActionScript 8 0.002 AppleScript 8 0.002 COBOL 8 0.002 EmberScript 8 0.002 Genshi 8 0.002 Hy 8 0.002 Idris 8 0.002 LiveScript 8 0.002 M 8 0.002 Mako 8 0.002 Max 8 0.002 Meson 8 0.002 Modelica 8 0.002 Open Policy Agent 8 0.002 Pan 8 0.002 RAML 8 0.002 Ragel in Ruby Host 8 0.002 SMT 8 0.002 Smali 8 0.002 Standard ML 8 0.002 Uno 8 0.002 UnrealScript 8 0.002 VBScript 8 0.002 Xojo 8 0.002 AGS Script 4 0.001 AngelScript 4 0.001 Bluespec 4 0.001 Brainfuck 4 0.001 CLIPS 4 0.001 CSON 4 0.001 Csound Document 4 0.001 Dylan 4 0.001 E 4 0.001 FORTRAN 4 0.001 Forth 4 0.001 G-code 4 0.001 GDB 4 0.001 Isabelle 4 0.001 Kit 4 0.001 LFE 4 0.001 LLVM 4 0.001 LOLCODE 4 0.001 LabVIEW 4 0.001 Lean 4 0.001 Lex 4 0.001 MQL5 4 0.001 NewLisp 4 0.001 ObjectScript 4 0.001 OpenSCAD 4 0.001 Perl6 4 0.001 Processing 4 0.001 Ragel 4 0.001 Ring 4 0.001 SAS 4 0.001 ShaderLab 4 0.001 XQuery 4 0.001 wdl 4 0.001 Total 461,406 100.000

13 A Differences in means

Table A3—Characteristics of Users: Geocoded vs. Out of Sample (Commits Sample)

(1) (2) (3) T-test Geocoded Out of sample Total Difference Variable Mean/SE Mean/SE Mean/SE (1)-(2) User age (’00 days) 24.394 19.046 21.023 5.347*** (0.410) (0.000) (1.321) Public repos 39.060 16.493 24.833 22.567*** (2.146) (0.000) (5.596) Followers 69.352 13.582 34.192 55.770*** (13.120) (0.000) (14.844) Following 23.229 4.840 11.636 18.389*** (2.760) (0.000) (4.610) Gists 9.612 3.560 5.797 6.051*** (1.418) (0.000) (1.567) 1listed Company 0.498 0.072 0.230 0.426*** (0.018) (0.000) (0.105) 1Organization 0.007 0.009 0.008 -0.002 (0.001) (0.000) (0.001) N 16591 28303 44894 Clusters 139 1 140

Notes: Table summarizes the user-level characteristics for the micro-sample originating from the commits log records. Columns (1)–(2) show the means for the geocoded sample used in the analyses and the out-of-geocoded sample (those not successfully geocoded). Column (3) shows the means for both combined. Column (4) shows the difference of column (1) and column (2). ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

14 Table A4—Characteristics of Users: Geocoded vs. Out of Sample (Pull Requests Sample)

(1) (2) (3) T-test Geocoded Out of sample Total Difference Variable Mean/SE Mean/SE Mean/SE (1)-(2) User age (’00 days) 23.561 17.051 20.815 6.510*** (0.039) (0.050) (0.032) Public repos 44.250 23.914 35.673 20.337*** (0.303) (0.950) (0.438) Followers 68.666 18.529 47.520 50.136*** (2.469) (1.463) (1.557) Following 24.255 6.882 16.928 17.373*** (0.635) (0.215) (0.379) Gists 15.688 3.806 10.676 11.882*** (3.807) (0.115) (2.202) 1listed Company 0.579 0.142 0.394 0.437*** (0.002) (0.002) (0.001) 1Organization 0.000 0.000 0.000 0.000 (0.000) (0.000) (0.000) N 69743 50871 120614

Notes: Table summarizes the user-level characteristics for the micro-sample originating from the pull requests log records. Columns (1)–(2) show the means for the geocoded sample used in the analyses and the out-of- geocoded sample (those not successfully geocoded). Column (3) shows the means for both combined. Column (4) shows the difference of column (1) and column (2). ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and10 percent level, respectively.

15 Table A5—Individual Characteristics, Commits Sample

(1) (2) (3) (4) T-test No WFH RCMD WFH Required WFH Total Difference Variable Mean/SE Mean/SE Mean/SE Mean/SE (1)-(2) (1)-(3) User age (’00 days) 25.031 25.723 24.397 24.816 -0.693* 0.634*** (0.399) (0.627) (0.459) (0.447) Public repos 40.148 46.394 39.578 40.605 -6.246** 0.571 (1.933) (4.486) (2.598) (2.068) Followers 70.256 91.389 81.778 78.050 -21.132 -11.522 (11.411) (16.538) (18.220) (13.592) Following 23.695 26.329 25.175 24.687 -2.634 -1.481 (2.765) (2.724) (3.801) (2.941) Gists 11.131 16.659 8.565 10.578 -5.529 2.566 (1.720) (4.670) (1.100) (1.644) 1Organization 0.006 0.007 0.007 0.007 -0.002 -0.001 (0.001) (0.002) (0.001) (0.001) 1listed Company 0.513 0.501 0.510 0.510 0.011 0.002 (0.023) (0.045) (0.016) (0.020) N 9317 2565 10301 22183 Clusters 117 46 105 125

Notes: Summary of the commits micrsample for the three groups in columns (1)–(3): No WFH, recommended WFH, and required WFH (where OxCGRT’s WFH coding = 2,3). Column (4) reports summary statistics for all. Columns (5)–(6) reports differences n means with No WFH as the baseline. N refers to the number of active individual-group cells recorded. Standard errors are clustered at the country level. ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

Table A6—Repository Characteristics, Commits Sample

(1) (2) (3) (4) T-test No WFH RCMD WFH Required WFH Total Difference Variable Mean/SE Mean/SE Mean/SE Mean/SE (1)-(2) (1)-(3) Repo age (’00 days) 15.767 16.192 15.652 15.765 -0.425*** 0.116 (0.299) (0.351) (0.332) (0.315) Contributors 12.492 13.778 12.096 12.465 -1.286*** 0.396*** (0.504) (0.618) (0.568) (0.535) Contributions (by others, ’00) 15.714 23.968 14.551 16.169 -8.254*** 1.162*** (1.552) (3.106) (1.619) (1.728) 1Forked 0.046 0.053 0.046 0.047 -0.007* 0.000 (0.006) (0.006) (0.006) (0.006) Stars (’00) 10.573 14.926 10.411 11.019 -4.353*** 0.161 (1.453) (2.287) (1.391) (1.500) Forks 266.767 411.449 259.944 280.934 -144.682*** 6.823 (29.022) (57.259) (31.415) (32.132) Open issues 49.872 76.918 47.301 51.928 -27.046*** 2.571** (5.428) (11.444) (5.452) (6.054) N 10958 3089 11812 25859 Clusters 140 96 139 161

Notes: Summary of the commits micrsample for the three groups in columns (1)–(3): No WFH, recommended WFH, and required WFH (where OxCGRT’s WFH coding = 2,3). Column (4) reports summary statistics for all. Columns (5)–(6) reports differences n means with No WFH as the baseline. N refers to the number of active repository-group cells recorded. Standard errors are clustered by programming language. ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

16 Table A7—Individual Characteristics, Pulls Sample

(1) (2) (3) (4) T-test No WFH RCMD WFH Required WFH Total Difference Variable Mean/SE Mean/SE Mean/SE Mean/SE (1)-(2) (1)-(3) User age (’00 days) 25.027 24.579 23.924 24.334 0.449 1.103*** (0.463) (0.514) (0.596) (0.526) Public repos 52.839 52.480 46.285 49.020 0.359 6.554*** (1.840) (2.961) (1.404) (1.437) Followers 84.128 73.416 79.744 80.221 10.712 4.384 (9.638) (5.218) (10.037) (8.820) Following 27.855 23.959 25.432 25.957 3.897** 2.424 (1.372) (1.833) (2.135) (1.630) Gists 27.259 16.814 12.578 17.460 10.445 14.681 (12.439) (2.389) (1.265) (4.023) 1Organization 0.000 0.000 0.000 0.000 0.000* -0.000 (0.000) (0.000) (0.000) (0.000) 1listed Company 0.599 0.598 0.593 0.596 0.001 0.006 (0.016) (0.025) (0.018) (0.017) N 22682 9926 44222 76830 Clusters 130 64 125 144

Notes: Summary of the pull requests microsample for the three groups in columns (1)–(3): No WFH, recommended WFH, and required WFH (where OxCGRT’s WFH coding = 2,3). Column (4) reports summary statistics for all. Columns (5)–(6) reports differences n means with No WFH as the baseline. N refers to the number of active individual-group cells recorded. Standard errors are clustered at the country level. ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

Table A8—Repository Characteristics, Pulls Sample

(1) (2) (3) (4) T-test No WFH RCMD WFH Required WFH Total Difference Variable Mean/SE Mean/SE Mean/SE Mean/SE (1)-(2) (1)-(3) Repo age (’00 days) 17.088 17.419 16.983 17.086 -0.331*** 0.105*** (0.427) (0.470) (0.419) (0.429) Contributors 14.594 17.831 15.298 15.471 -3.238*** -0.704*** (0.223) (0.191) (0.231) (0.214) Contributions (by others, ’00) 6.235 11.327 9.149 8.546 -5.092*** -2.914*** (0.589) (0.924) (0.793) (0.741) 1Forked 0.030 0.020 0.027 0.026 0.010*** 0.003*** (0.003) (0.003) (0.003) (0.003) Stars (’00) 7.769 14.693 10.170 10.106 -6.924*** -2.401*** (1.169) (2.316) (1.331) (1.427) Forks 146.011 282.523 213.026 202.230 -136.512*** -67.015*** (15.376) (29.759) (18.775) (19.070) Open issues 28.075 53.029 40.835 38.614 -24.954*** -12.759*** (2.010) (3.781) (2.920) (2.699) N 23760 11583 37580 72923 Clusters 153 116 184 200

Notes: Summary of the pull requests microsample for the three groups in columns (1)–(3): No WFH, recommended WFH, and required WFH (where OxCGRT’s WFH coding = 2,3). Column (4) reports summary statistics for all. Columns (5)–(6) reports differences n means with No WFH as the baseline. N refers to the number of active repository-group cells recorded. Standard errors are clustered by programming language. ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

17 Table A9—US vs Rest of World Individual Characteristics From Commits Sample

(1) (2) (3) T-test US Rest of world Total Difference Variable Mean/SE Mean/SE Mean/SE (1)-(2) User age (’00 days) 25.677 24.103 24.417 1.574*** (0.000) (0.411) (0.424) Public repos 38.376 39.113 38.966 -0.737 (0.000) (2.728) (2.199) Followers 75.611 69.046 70.355 6.565 (0.000) (16.953) (13.494) Following 19.829 24.296 23.406 -4.467 (0.000) (3.220) (2.749) Gists 11.303 9.188 9.610 2.115 (0.000) (1.761) (1.461) 1Organization 0.010 0.006 0.007 0.004*** (0.000) (0.001) (0.001) 1listed Company 0.569 0.481 0.499 0.088*** (0.000) (0.016) (0.019) N 3194 12829 16023 Clusters 1 124 125 Notes: Table summarizes the individual characteristics for US-mapped observations vs the rest of the world, for observations in the commits micro-sample. Columns (1), (2), & (3) reports summary statistics for the US sample, rest of world, and both combined, respectively. Column (4) shows the difference of US vs rest of world. ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

18 Table A10—US vs Rest of World Repository Characteristics From Commits Sample

(1) (2) (3) T-test US Rest of world Total Difference Variable Mean/SE Mean/SE Mean/SE (1)-(2) Repo age (’00 days) 15.779 15.602 15.641 0.177 (0.408) (0.300) (0.317) Contributors (’00) 11.613 11.508 11.531 0.105 (0.584) (0.484) (0.485) Contributions (by others, ’00) 12.314 12.101 12.147 0.213 (1.886) (1.152) (1.256) 1Forked 0.049 0.044 0.045 0.005 (0.008) (0.005) (0.005) Stars (’00) 8.331 9.190 9.004 -0.859 (1.251) (1.306) (1.193) Forks 204.346 220.482 216.983 -16.135 (37.333) (23.247) (23.077) Open issues 38.990 38.857 38.886 0.133 (4.913) (3.982) (4.060) N 4011 14488 18499 Clusters 94 147 161 Notes: Table summarizes the repository characteristics for US-mapped observations vs the rest of the world, for observations in the commits micro-sample. Columns (1), (2), & (3) reports summary statistics for the US sample, rest of world, and both combined, respectively. Column (4) shows the difference of US vs rest of world. ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

19 Table A11—US vs Rest of World Individual Characteristics From Pulls Sample

(1) (2) (3) T-test US Rest of world Total Difference Variable Mean/SE Mean/SE Mean/SE (1)-(2) User age (’00 days) 25.312 23.413 23.929 1.898*** (0.000) (0.534) (0.536) Public repos 48.586 43.976 45.228 4.610*** (0.000) (1.404) (1.373) Followers 98.597 61.505 71.577 37.093*** (0.000) (6.433) (8.637) Following 21.634 25.248 24.266 -3.613** (0.000) (1.796) (1.498) Gists 15.285 16.959 16.505 -1.674 (0.000) (6.376) (4.654) 1Organization 0.000 0.000 0.000 -0.000** (0.000) (0.000) (0.000) 1listed Company 0.637 0.563 0.583 0.075*** (0.000) (0.010) (0.017) N 17116 45914 63030 Clusters 1 143 144 Notes: Table summarizes the individual characteristics for US-mapped observations vs the rest of the world, for observations in the pull requests micro-sample. Columns (1), (2), & (3) reports summary statistics for the US sample, rest of world, and both combined, respectively. Column (4) shows the difference of US vs rest of world. ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

20 Table A12—US vs Rest of World Individual Characteristics From Repository Sample

(1) (2) (3) T-test US Rest of world Total Difference Variable Mean/SE Mean/SE Mean/SE (1)-(2) Repo age (’00 days) 16.763 16.953 16.899 -0.190 (0.484) (0.370) (0.399) Contributors (’00) 14.657 13.724 13.990 0.933*** (0.302) (0.188) (0.206) Contributions (by others, ’00) 10.543 7.292 8.219 3.251*** (0.909) (0.784) (0.780) 1Forked 0.030 0.030 0.030 -0.000 (0.003) (0.003) (0.003) Stars (’00) 10.661 7.601 8.474 3.061*** (1.288) (1.050) (1.079) Forks 247.145 148.990 176.995 98.155*** (23.048) (14.227) (15.438) Open issues 48.670 29.412 34.906 19.258*** (4.941) (2.109) (2.615) N 14242 35675 49917 Clusters 135 179 200 Notes: Table summarizes the repository-level characteristics for the micro-sample originating from the pull requests log records. Columns (1)–(2) show the means for the geocoded sample used in the analyses and the out-of-geocoded sample (those not successfully geocoded). Column (3) shows the means for both combined. Column (4) shows the difference of column (1) and column (2). ∗∗∗, ∗∗, and ∗ denotes significance at the 1, 5, and 10 percent level, respectively.

21 B Benchmarking

Figure A9: Commits in January 2020. Notes. Path plot (unsmoothed) of commits in January 2020. Red solid line is the activity level of users that are successfully geocoded to a country or U.S. state; Black dotted line is the activity level of users that cannot be geocoded. Gray vertical bars indicate weekends (Sat–Sun).

(a) U.S. sample (b) Non-U.S. sample Figure A10: Day (U.S. sample vs. others) Notes. Path plot (unsmoothed) of commits around Jan–Feb 2020 for U.S. sample vs. others. First black dashed line indicates Martin Luther King Jr. Day on 20 Jan; second one indicates Washington’s Birthday on 17 Feb. Both occur on Mondays. Horizontal lines show the Monday average over the shown sample period, excluding the two Monday holidays. Gray vertical bars indicate weekends (Sat–Sun).

22 2500 180 Spring Bank Holiday Spring Bank Holiday (Mon, 25 May) (Mon, 25 May) 120 1500

VE Day 60 Early May Bank Holiday (Fri, 8 May) VE Day Early May Bank Holiday (Fri, 8 May) 0 29Apr 6May 13May 20May 27May 3Jun 10Jun 29Apr500 6May 13May 20May 27May 3Jun 10Jun (a) UK sample (b) Non-UK sample Figure A11: May Bank Holidays (UK sample vs. others) Notes. Path plot (unsmoothed) of commits around May 2020 for U.K. sample vs. others. First black dashed line indicates Early May Bank Holiday on 8 May, which has been brought back to coincide with the Victory in Europe Day; second black dashed line one indicates the Spring Bank Holiday on 25 May. Gray vertical bars indicate weekends (Sat–Sun).

Chinese New Year 16 days (including eve) Chinese New Year 16 days (including eve)

(24 Jan - 8 Feb) 3000

400 (24 Jan - 8 Feb) 2000 200 1000

0 1Jan 15Jan 29Jan 12Feb 26Feb

0 24Jan 8Feb 1Jan 15Jan 24Jan 29Jan 8Feb 12Feb 26Feb (b) Other countries (a) Countries celebrating CNY Figure A12: Chinese New Year Holidays Notes. Path plot (unsmoothed) of commits around Jan–Feb 2020, with the gray area indicating the Chinese New Year (CNY) period over a 15-days period plus the eve, 24 Jan–8 Feb. Subfigure (a) includes countries that celebrate the CNY: China, Indonesia, Korea, Malaysia, Singapore, and Vietnam. Majority of these are from China. Subfigure (b) includes all users from all other countries.

23 C Event studies

.1 .15

.05 .1

.05 0

0 -.05

-.05 -.1 -21 -14 -7 0 7 14 21 -21 -14 -7 0 7 14 21 Days relative to enforced WFH Days relative to enforced WFH (a) Log opened issues per user (b) Log closed issues per user .4 .4

.2 .2

0 0

-.2 -.2 -21 -14 -7 0 7 14 21 -21 -14 -7 0 7 14 21 Days relative to enforced WFH Days relative to enforced WFH (c) Log opened issues (d) Log closed issues .4 .4

.2 .2

0 0

-.2 -.2 -21 -14 -7 0 7 14 21 -21 -14 -7 0 7 14 21 Days relative to enforced WFH Days relative to enforced WFH (e) Log users (opened issues) (f) Log users (closed issues) Figure A13: Event Studies for Opening and Closing of Issues Notes—Event studies documenting changes in opened closed issues. Day 0 is the date at which the OxCGRT WFH indicator for a country first switches from either a 0 or 1 to a 2 or 3. In the last row, the dependent variable is the log of (1+) the number of recordedusersforthe respective type of activity (column-wise). All results control for timing group-by-week, date, and country fixed effects, the OxCGRT WFH indicator, two OxCGRT government COVID-19 response indices, and the COVID-19 epidemiology records. Shaded gray areas denote 90% confidence band constructed from standard errors clustered by countries.

24 (a) Japan

(b) Sweden (c) Taiwan Figure A14: Base countries’ path plot Notes. Path of user activity for those located in Japan, Sweden, and Taiwan—three notable countries that never imposed lockdown/closure of workplaces in the sample period. The vertical lines indicate general periods of global lockdown (see Figures A5 and A6). Variables winsorized at 5% and 95%. Line plots are from locally weighted scatterplot smoothing with the stated bandwidths.

25 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A15: Austria’s path plot Notes. Path of user activity for those located in Austria (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). Austria imposed mandatory WFH for all-but-essential workplaces (WFH = 3) on March 16; and then relaxed this to mandatory WFH for some sectors (WFH = 2) starting April 14. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

26 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A16: Belgium’s path plot Notes. Path of user activity for those located in Belgium (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). Belgium imposed mandatory WFH for some sectors (WFH = 2) starting March 14, expanded this to all-but-essential workplaces (WFH = 3) on March 18, and then back to mandatory WFH for some sectors on May 11. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

27 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A17: Canada’s path plot Notes. Path of user activity for those located in Canada (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). Canada imposed mandatory WFH for all-but-essential workplaces (WFH = 3) on March 18, and then relaxed this to mandatory WFH for some sectors (WFH = 2) starting June 22. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

28 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A18: China’s path plot Notes. Path of user activity for those located in China (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). China imposed mandatory WFH for all-but-essential workplaces (WFH = 3) on January 26, relaxed to mandatory WFH for some sectors (WFH = 2) on April 3, and then back to mandatory WFH for all-but-essential workplaces on May 10. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

29 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A19: France’s path plot Notes. Path of user activity for those located in France (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). France imposed mandatory WFH for all-but-essential workplaces on March 17, then decreased it to mandatory WFH for some sectors (WFH = 2) on May 11, and finally to a recommended WFH (WFH = 1) on June 22. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

30 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A20: Germany’s path plot Notes. Path of user activity for those located in Germany (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). Germanyimposed mandatory WFH for some sectors on March 22 (WFH = 2). The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

31 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A21: Italy’s path plot Notes. Path of user activity for those located in Italy (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). Italy imposed mandatoryfor all-but-essential workplaces (WFH = 3) on February 22, relaxed to recommended WFH (WFH = 1) on May 4, and up again to mandatory WFH for some sectors (WFH = 2) on May 16. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

32 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A22: Netherlands’ path plot Notes. Path of user activity for those located in Netherlands’ (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). Netherlands’ imposed mandatory for all-but-essential workplaces (WFH = 3) on March 15, then relaxed to mandatory WFH for some sectors (WFH = 2) on May 11. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period)are shown in gray as reference. Variables winsorized at 5% and 95%.

33 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A23: Norway’s path plot Notes. Path of user activity for those located in Norway (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). Norway imposed mandatory WFH for some sectors (WFH = 2) on March 12, then relaxed to recommended WFH (WFH = 1) on June 2. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

34 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A24: Spain’s path plot Notes. Path of user activity for those located in Spain (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). Spain imposed mandatory WFH for some sectors (WFH = 2) on March 14, increased to mandatory for all-but-essential workplaces (WFH = 3) on March 30, then relaxed back to mandatory WFH for some sectors on May 22. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

35 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A25: United Kingdom’s path plot Notes. Path of user activity for those located in United Kingdom (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). UnitedKingdom imposed mandatory WFH for all-but-essential workplaces (WFH = 3) on March 21, and then relaxed to mandatory WFH for some sectors (WFH = 2) on May 29. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

36 (a) Commits per user-repo

(b) Commits (c) Active user-repos Figure A26: United States’ path plot Notes. Path of user activity for those located in the United States (blue solid line), using Lowess smoothing on individual records aggregated up to the daily level.. Values are subfigure (a) is equivalent to values in subfigure (b) divided by values in subfigure (c). TheUnitedStates imposed mandatory WFH for all-but-essential workplaces (WFH = 3) on March 19, then relaxed to mandatory WFH for some sectors (WFH = 2) on June 15. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

37 (a) Austria’s path plot (b) Belgium’s path plot

(c) Canada’s path plot (d) China’s path plot

(e) France’s path plot (f) Germany’s path plot Figure A27: Pull requests [part 1] Notes. Path plots of pull requests per user-repo using Lowess smoothing on individual records aggregated up to the daily level. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

38 (a) Italy’s path plot (b) Netherlands’ path plot

(c) Norway’s path plot (d) Spain’s path plot

(e) United Kingdom’s path plot (f) United States’ path plot Figure A28: Pull requests [part 2] Notes. Path plots of pull requests per user-repo using Lowess smoothing on individual records aggregated up to the daily level. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

39 (a) Austria’s path plot (b) Belgium’s path plot

(c) Canada’s path plot (d) China’s path plot

(e) France’s path plot (f) Germany’s path plot Figure A29: Opened issues [part 1] Notes. Path plots of opened issues per user-repo using Lowess smoothing on individual records aggregated up to the daily level. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

40 (a) Italy’s path plot (b) Netherlands’ path plot

(c) Norway’s path plot (d) Spain’s path plot

(e) United Kingdom’s path plot (f) United States’ path plot Figure A30: Opened issues [part 2] Notes. Path plots of opened issues per user-repo using Lowess smoothing on individual records aggregated up to the daily level. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

41 (a) Austria’s path plot (b) Belgium’s path plot

(c) Canada’s path plot (d) China’s path plot

(e) France’s path plot (f) Germany’s path plot Figure A31: Closed issues [part 1] Notes. Path plots of closed issues per user-repo using Lowess smoothing on individual records aggregated up to the daily level. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

42 (a) Italy’s path plot (b) Netherlands’ path plot

(c) Norway’s path plot (d) Spain’s path plot

(e) United Kingdom’s path plot (f) United States’ path plot Figure A32: Closed issues [part 2] Notes. Path plots of closed issues per user-repo using Lowess smoothing on individual records aggregated up to the daily level. The path of Japan, Sweden, and Taiwan (three notable countries that never imposed mandatory WFH in the commits sample period) are shown in gray as reference. Variables winsorized at 5% and 95%.

43 D Geocoding examples

Table A13—Random examples of failed geocoding

Location independent Bangalore, Remote Just here on Earth… for now Jerome Library, BGSU Campus @ransty Tokyo, Hangzhou, Canberra 5602 Research Park Blvd, Suite 300, Madison, WI 53719 San Francisco, CA, USA - Paris, FR - Lyon, FR The Linked Open Data Cloud :-) Vancouver / SF / NYC Vilnius/Kybartai, Lithuania Boujailles - Haut-Doubs - France Alphabit SF | NYC | Remote In your apps Egypt, Monofeya, Quesna The Wired | Everywhere Edinburgh / Berlin World/Montreal/NYC Sofia, Montevideo, Tokyo, London, Bangalore, Cranbury Stuck in a infinite loop 77 Massachusetts Ave, Bldg 37 Room 447, Cambridge, MA 02139 United Nations (OCHA), New York Moscow + Dessau Nederland aka The Netherlands Greater Boston area, Massachusetts Home - where I work from. Greater New York Area; Tulsa, OK Paris, Thailand, Hong Kong Potland, OR, USA In your website Toronto, New York City, Boston, Portland Shanghai,mainland China London/Berlin/Oxford Leiden / The Hague / Utrecht, The Netherlands 3900 W Alameda Ave, Suite 1200, Burbank CA Belgium, Netherlands, Romania, Germany, Austria, Italy, Czech Republic 幻ちょあ鄉 Dallas, Texas, USA, 3rd Rock, Sol, … Virgo Super-Cluster, Universe Somewhere in northern Italy Greater New York City Area, USA UoN Towers, 12th Floor; Nairobi, Kenya Snodak San Francisco, CA & Boston, MA Detroit - Graz - Mainz Pennsylvania State University, University Park, PA relocating to Europe Toulouse, Paris, Grenoble, everywhere Non Euclidean Hellscape

44 Table A14—Random sample of 100 confidence=1 samples (100% accuracy)

Location string Geocoded country Geocoded state Bangkok, Thailand. Thailand กรุงเทพมหานคร Serres, Greece Greece Αποκεντρωμένη Διοίκηση Μακεδονίας - Θράκης SuZhou, JiangSu China 江苏省 Sorocaba/São Paulo/Brasil Brazil São Paulo izmir, Turkey Turkey — Brazil, Rio Grande do Sul Brazil Rio Grande do Sul china China — Salzburg, Austria Austria Salzburg Itu/SP Brazil São Paulo Russia, Kirov Russian Federation Кировская область Warsaw (Poland) Poland województwo mazowieckie London,UK United Kingdom England Izmir / Turkey Turkey — chengdu, sichuan China 四川省 武汉, CN China 湖北省 Venezia / Italy Italy Veneto Santa Rosa, CA, USA United States of America California Jia Ding,Shang Hai China 上海市 NYC, NY US United States of America New York Calgary, Alberta Canada Alberta Houston, USA United States of America Texas Medan, Indonesia Indonesia Sumatera Utara Ciudad de México Mexico Ciudad de México DAEJEON, Republic of Korea Korea, Republic of — near Frankfurt, Germany Germany Hessen Canton Province, China China 广东省 Austin, TX United States of America Texas Phoenix Arizona US United States of America Arizona Campinas - SP - Brazil Brazil São Paulo Linz / Austria Austria Oberösterreich Asturias Spain Asturias / Asturies Malatya Turkey Malatya Bulgaria Bulgaria — Shenyang City,Liaoning Province,China China 辽宁省 Israel. Israel — INDIA India — Toyota, Aichi Japan. Japan — Medan Indonesia Sumatera Utara Nicaragua Nicaragua — Republic of Belarus Belarus — Montreal / QC - Canada Canada Québec Recife - PE - Brazil Brazil Pernambuco Thuringia, Germany Germany Thüringen Campinas, SP - Brazil Brazil São Paulo Kashiwa, Japan Japan — West Cork, Ireland Ireland — Boise, Idaho USA United States of America Idaho New Orleans, USA United States of America Louisiana San Jose CA United States of America California Hangzhou, Zhejiang, China China 浙江省 Mayenne (France) France Pays de la Loire Ourense (Galicia) Spain Galicia / Galiza ChaoAn China 广东省 Boston, Mass United States of America Massachusetts İzmir / Turkey Turkey — Jaipur, Rajasthan, India India Rajasthan Miskolc, Hungary Hungary — Germany Germany — Vigo (Spain) Spain Galicia / Galiza Toronto ON, Canada Canada Ontario Des Moines„ IA United States of America Iowa Braga, Portugal Portugal Norte Cape Town - SA South Africa Western Cape Kiev/Ukraine Ukraine — 重庆 China 重庆市 north america — — Morelia, Mexico Mexico Michoacán de Ocampo Castellón, Spain Spain Comunitat Valenciana Kingsville, Ontario Canada Ontario Continued on next page

45 Table A14 – Continued from previous page Location string Geocoded country Geocoded state The UK United Kingdom — Toowoomba, Australia Australia Queensland São Paulo/SP - BR Brazil São Paulo Philippines Philippines — Squamish, BC, Canada Canada British Columbia Hang Zhou China 浙江省 China Zhejiang Shaoxing China 浙江省 buenos aires Argentina — La Paz, Bolivia Bolivia (Plurinational State of) La Paz Mazatlan, Mexico Mexico Sinaloa Porto Alegre, RS - Brazil Brazil Rio Grande do Sul Santa Fe Argentina Santa Fe Washington, D.C. United States of America District of Columbia Berlin Area, Germany Germany — São Paulo/SP - Brasil Brazil São Paulo San Francisco Bay Area, California, USA United States of America California Valais, Switzerland Switzerland Valais/Wallis Saint Petersburg, Russia Russian Federation Санкт-Петербург Winston-Salem, NC United States of America North Carolina Taipei (Taiwan) Taiwan, Province of China 臺北市 Praia Grande / São Paulo / Brasil Brazil São Paulo Spain - Valencia Spain Comunitat Valenciana Saigon, Vietnam Viet Nam — NL Netherlands — Suzhou, Jiangsu, China China 江苏省 Tulsa, OK United States of America Oklahoma NJ USA United States of America New Jersey Joinville, SC, Brazil Brazil Santa Catarina Salvador, Bahia - Brasil Brazil Bahia Denver, Co United States of America Colorado Kursk, Russia Russian Federation Курская область

46 Table A15—Random sample of 100 confidence=2 samples (100% accuracy) Location string Geocoded country Geocoded state Paris, TX United States of America Texas Lafayette, Louisiana, USA United States of America Louisiana South Bend, Indiana United States of America Indiana Rzeszów, Poland Poland województwo podkarpackie Mainz & Köln Germany Rheinland-Pfalz Treves (Germany) Germany Rheinland-Pfalz Murrieta, CA United States of America California Ivanovo, Russia Russian Federation Ивановская область Paris (France) France Île-de-France Cruz das Almas Brazil Bahia Baltimore, Maryland, USA United States of America Maryland Sioux Falls, SD United States of America South Dakota Skopje, Macedonia North Macedonia Скопски СР Caloocan City Philippines — Namur, Belgium Belgium Wallonie Rochester, Ny United States of America New York Las Palmas De Gran Canaria Spain — Paris France Île-de-France Manchester, NH United States of America New Hampshire brooklyn, new york United States of America New York Tuebingen, Germany Germany Baden-Württemberg Nampa, Idaho United States of America Idaho Miami, Fl United States of America Florida Kawagoe, Japan Japan — Redlands, California, USA United States of America California New Smyrna Beach, FL USA United States of America Florida Pittsburgh, Pennsylvania United States of America Pennsylvania Farmington, NM United States of America New Mexico General Trias, Cavite Philippines Cavite Göttingen Germany Niedersachsen Hsinchu, Taiwan Taiwan, Province of China 臺灣省 Feira Nova - PE Brazil Pernambuco Santa Barbara United States of America California The Hague, Netherlands Netherlands Zuid-Holland Lugano Switzerland Ticino Italy - Milano Italy Lombardia Palo Alto, CA US United States of America California Tangerang Selatan, Indonesia Indonesia Banten Santa Barbara, USA United States of America California Miami, Florida United States of America Florida Rybinsk Russian Federation Ярославская область Barcelona (SPAIN) Spain Catalunya Pittsburgh, Pa United States of America Pennsylvania Miami, FL. USA United States of America Florida Rzeszow, Poland Poland województwo podkarpackie Moldova, Chisinau Moldova, Republic of — Liverpool, England United Kingdom England Cheyenne, WY United States of America Wyoming Weiden in der Oberpfalz, Germany Germany Bayern Milan area, Italy Italy Lombardia Barcelona Spain Catalunya Melbourne, FL United States of America Florida Osnabrück Germany Niedersachsen Lewiston, ME United States of America Maine Moncton, NB Canada New Brunswick Rabat Morocco — Palo Alto CA, USA United States of America California Deventer, Netherlands Netherlands Overijssel Enschede, The Netherlands Netherlands Overijssel Milano (IT) Italy Lombardia Funabashi, Japan Japan — Redlands, CA United States of America California Saint-Etienne, France France Auvergne-Rhône-Alpes Winsen (Luhe) Germany Niedersachsen Pittsburgh,PA, USA United States of America Pennsylvania Salford, Greater Manchester United Kingdom England Continued on next page

47 Table A15 – Continued from previous page Location string Geocoded country Geocoded state Nordhausen Germany Thüringen Hague Netherlands Zuid-Holland Milano - Italy Italy Lombardia Palo Alto United States of America California SeongNam city Korea, Republic of — Turin, Italy Italy Piemonte pittsburgh, pa United States of America Pennsylvania Newcastle, UK United Kingdom England Horten Norway — Pegnitz, Germany Germany Bayern Germany / Bochum Germany Nordrhein-Westfalen Paris area, France France Île-de-France Zwolle Netherlands Overijssel Germany, Kaiserslautern Germany Rheinland-Pfalz Minneapolis,MN United States of America Minnesota Mönchengladbach, Germany Germany Nordrhein-Westfalen Douglasville, GA, USA United States of America Georgia Clovis, CA United States of America California Las Palmas, Spain Spain — Skopje, North Macedonia North Macedonia Скопски СР The Hague, NL Netherlands Zuid-Holland Eugene, OR, 97405, USA United States of America Oregon Annecy, France France Auvergne-Rhône-Alpes Ahaus, DE Germany Nordrhein-Westfalen Miami, FL, USA United States of America Florida Russian Federation Sarov Russian Federation Нижегородская область Mönchengladbach Germany Nordrhein-Westfalen Eugene Oregon United States of America Oregon Maribor, Slovenia Slovenia — Ås, Norway Norway — Bristol, UK United Kingdom England Limoges France Nouvelle-Aquitaine Decatur, IL 62521 United States of America Illinois Paris, France France Île-de-France

48 Table A16—Random sample of 100 confidence=2 samples (100% accuracy) Location string Geocoded country Geocoded state Paris, TX United States of America Texas Lafayette, Louisiana, USA United States of America Louisiana South Bend, Indiana United States of America Indiana Rzeszów, Poland Poland województwo podkarpackie Mainz & Köln Germany Rheinland-Pfalz Treves (Germany) Germany Rheinland-Pfalz Murrieta, CA United States of America California Ivanovo, Russia Russian Federation Ивановская область Paris (France) France Île-de-France Cruz das Almas Brazil Bahia Baltimore, Maryland, USA United States of America Maryland Sioux Falls, SD United States of America South Dakota Skopje, Macedonia North Macedonia Скопски СР Caloocan City Philippines — Namur, Belgium Belgium Wallonie Rochester, Ny United States of America New York Las Palmas De Gran Canaria Spain — Paris France Île-de-France Manchester, NH United States of America New Hampshire brooklyn, new york United States of America New York Tuebingen, Germany Germany Baden-Württemberg Nampa, Idaho United States of America Idaho Miami, Fl United States of America Florida Kawagoe, Japan Japan — Redlands, California, USA United States of America California New Smyrna Beach, FL USA United States of America Florida Pittsburgh, Pennsylvania United States of America Pennsylvania Farmington, NM United States of America New Mexico General Trias, Cavite Philippines Cavite Göttingen Germany Niedersachsen Hsinchu, Taiwan Taiwan, Province of China 臺灣省 Feira Nova - PE Brazil Pernambuco Santa Barbara United States of America California The Hague, Netherlands Netherlands Zuid-Holland Lugano Switzerland Ticino Italy - Milano Italy Lombardia Palo Alto, CA US United States of America California Tangerang Selatan, Indonesia Indonesia Banten Santa Barbara, USA United States of America California Miami, Florida United States of America Florida Rybinsk Russian Federation Ярославская область Barcelona (SPAIN) Spain Catalunya Pittsburgh, Pa United States of America Pennsylvania Miami, FL. USA United States of America Florida Rzeszow, Poland Poland województwo podkarpackie Moldova, Chisinau Moldova, Republic of — Liverpool, England United Kingdom England Cheyenne, WY United States of America Wyoming Weiden in der Oberpfalz, Germany Germany Bayern Milan area, Italy Italy Lombardia Barcelona Spain Catalunya Melbourne, FL United States of America Florida Osnabrück Germany Niedersachsen Lewiston, ME United States of America Maine Moncton, NB Canada New Brunswick Rabat Morocco — Palo Alto CA, USA United States of America California Deventer, Netherlands Netherlands Overijssel Enschede, The Netherlands Netherlands Overijssel Milano (IT) Italy Lombardia Funabashi, Japan Japan — Redlands, CA United States of America California Saint-Etienne, France France Auvergne-Rhône-Alpes Winsen (Luhe) Germany Niedersachsen Pittsburgh,PA, USA United States of America Pennsylvania Salford, Greater Manchester United Kingdom England Continued on next page

49 Table A16 – Continued from previous page Location string Geocoded country Geocoded state Nordhausen Germany Thüringen Hague Netherlands Zuid-Holland Milano - Italy Italy Lombardia Palo Alto United States of America California SeongNam city Korea, Republic of — Turin, Italy Italy Piemonte pittsburgh, pa United States of America Pennsylvania Newcastle, UK United Kingdom England Horten Norway — Pegnitz, Germany Germany Bayern Germany / Bochum Germany Nordrhein-Westfalen Paris area, France France Île-de-France Zwolle Netherlands Overijssel Germany, Kaiserslautern Germany Rheinland-Pfalz Minneapolis,MN United States of America Minnesota Mönchengladbach, Germany Germany Nordrhein-Westfalen Douglasville, GA, USA United States of America Georgia Clovis, CA United States of America California Las Palmas, Spain Spain — Skopje, North Macedonia North Macedonia Скопски СР The Hague, NL Netherlands Zuid-Holland Eugene, OR, 97405, USA United States of America Oregon Annecy, France France Auvergne-Rhône-Alpes Ahaus, DE Germany Nordrhein-Westfalen Miami, FL, USA United States of America Florida Russian Federation Sarov Russian Federation Нижегородская область Mönchengladbach Germany Nordrhein-Westfalen Eugene Oregon United States of America Oregon Maribor, Slovenia Slovenia — Ås, Norway Norway — Bristol, UK United Kingdom England Limoges France Nouvelle-Aquitaine Decatur, IL 62521 United States of America Illinois Paris, France France Île-de-France

50 Table A17—Random sample of 100 confidence=3 samples (100% accuracy) Location string Geocoded country Geocoded state Udine, Italy Italy Friuli Venezia Giulia Fürth, Germany Germany Bayern Latvija, Liepaja Latvia Kurzeme Fareham United Kingdom England Tychy, Poland Poland województwo śląskie Tempe, AZ, USA United States of America Arizona Sankt Veit an der Glan, Austria Austria Kärnten Menlo Park, CA United States of America California Kalamazoo, Michigan, USA United States of America Michigan Stillwater, Oklahoma United States of America Oklahoma St. Paul, Minnesota United States of America Minnesota Den Bosch, Netherlands Netherlands Noord-Brabant Goshen, CT United States of America Connecticut firenze,Italy Italy Toscana Bemidji, MN United States of America Minnesota Russia, Gorno-Altaisk Russian Federation Республика Алтай Lafayette, IN United States of America Indiana Stupino, Russia Russian Federation Московская область Nottingham, U.K. United Kingdom England Kherson, Ukraine Ukraine Херсонська область Liège Belgium Wallonie Amersfoort, Nederland Netherlands Utrecht Lommel Belgium Vlaanderen Canoas, RS, Brazil. Brazil Rio Grande do Sul Pirna Germany Sachsen Zürich, Zurich, Switzerland Switzerland Zürich NANTES France Pays de la Loire Rehau / Germany Germany Bayern Eindhoven, NL Netherlands Noord-Brabant Roanoke, Virginia, USA United States of America Virginia Coburg, Germany Germany Bayern Walla Walla, WA United States of America Washington Bloomington, Illinois United States of America Illinois Klamath Falls, OR United States of America Oregon אביב תל מחוז Tel-Aviv Israel Nijmegen - The Netherlands Netherlands Gelderland Fort Lauderdale, FL, United States United States of America Florida Salem NH United States of America New Hampshire Manhattan, KS, USA United States of America Kansas Utrecht Area, The Netherlands Netherlands Utrecht Nantes (France) France Pays de la Loire Azov Russian Federation Ростовская область Idaho Falls United States of America Idaho Saint Paul, MN, USA United States of America Minnesota Lorgues France Provence-Alpes-Côte d’Azur Syracuse, NY, USA United States of America New York Winterthur Switzerland Zürich Mission Viejo United States of America California Rolla, MO United States of America Missouri Nijmegen. The Netherlands Netherlands Gelderland Penticton, British Columbia, Canada Canada British Columbia St-Germain en Laye, France France Île-de-France Hof Germany Bayern Freyung, Germany Germany Bayern Redwood City, CA United States of America California Vinhedo, Brazil Brazil São Paulo Boulder United States of America Colorado Hradec Králové Czechia Severovýchod Ruston, Louisiana United States of America Louisiana Manhattan, KS United States of America Kansas Cahors, France France Occitanie Croatia, Čakovec Croatia — DeLand, Florida United States of America Florida Vancouver, BC, Canada Canada British Columbia Vancouver, B.C. Canada British Columbia bozeman, MT United States of America Montana Continued on next page

51 Table A17 – Continued from previous page Location string Geocoded country Geocoded state Longmont, Co United States of America Colorado Tarnowskie Góry / Poland Poland województwo śląskie New Haven, CT United States of America Connecticut Livermore, CA, USA United States of America California Rovereto (TN), IT Italy Trentino-Alto Adige/Südtirol Willich Germany Nordrhein-Westfalen Fairbanks, Alaska United States of America Alaska St Paul, MN United States of America Minnesota Barueri - SP Brazil São Paulo Pasadena, California United States of America California Menlo Park, California United States of America California Wayne NJ USA United States of America New Jersey Roanoke, VA United States of America Virginia Lausanne (CH) Switzerland Vaud Glendale, CA Canada — Osasco, São Paulo - Brazil Brazil São Paulo Slidell, LA United States of America Louisiana Gießen Germany Hessen Morges, CH Switzerland Vaud Saint-Saturnin-les-Apt, France France Provence-Alpes-Côte d’Azur אביב תל מחוז Israel, Tel Aviv Israel 上海市普陀区 China 上海市 Ann Arbor, MI, United States United States of America Michigan Groton, MA United States of America Massachusetts Garner, NC United States of America North Carolina Havant, UK United Kingdom England Narashino, Chiba Japan — Norwell, MA United States of America Massachusetts The Netherlands, Eindhoven Netherlands Noord-Brabant Hollywood, FL United States of America Florida Versmold, Germany Germany Nordrhein-Westfalen Germany, Bad Reichenhall Germany Bayern Gießen, Germany Germany Hessen würzburg, germany Germany Bayern

52 Table A18—Random sample of 100, confidence=4 (99% accuracy)

Location string Geocoded country Geocoded state Austria, Vorarlberg, Dornbirn Austria Vorarlberg Harrisburg, PA United States of America Pennsylvania Hemer, Germany Germany Nordrhein-Westfalen Esporles, Spain Spain Illes Balears The Sun France Bretagne Åseda, Sweden Sweden Kronobergs län Manassas, VA, USA United States of America Virginia Essen, Antwerp, Belgium Belgium Vlaanderen Dijon, Bourgogne, France France Bourgogne-Franche-Comté Almada, Portugal Portugal Área Metropolitana de Lisboa Flensburg, Germany Germany Schleswig-Holstein Ismaning, Germany Germany Bayern Murter Croatia — North Richland Hills, Texas, USA United States of America Texas DE-27252 Schwaförden Germany Niedersachsen Frankenthal Germany Rheinland-Pfalz Comox, BC, Canada Canada British Columbia Providence, Rhode Island, USA United States of America Rhode Island Eichstätt, Germany Germany Bayern Centerville, OH United States of America Ohio Wolverhampton, UK United Kingdom England Newbury, UK United Kingdom England Killorglin, Ireland Ireland — Fürstenfeldbruck, Germany Germany Bayern Olympia Washington United States of America Washington La Jolla, CA United States of America California Hartford, CT US United States of America Connecticut Broxbourne United Kingdom England Marlow, UK United Kingdom England Brussels, BE Belgium Région de Bruxelles-Capitale - Brussels Hoofdstedelijk Gewest Best, The Netherlands Netherlands Noord-Brabant Foster City United States of America California Lake Forest United States of America Illinois Reston,VA United States of America Virginia Waltham, MA, USA United States of America Massachusetts Mirfield, United Kingdom United Kingdom England France (Lyon) France Auvergne-Rhône-Alpes Peachland, BC Canada British Columbia Posadas, Misiones, Argentina Argentina Misiones Albany, Oregon United States of America Oregon Solon, OH United States of America Ohio Hilversum, Netherlands Netherlands Noord-Holland Bluffdale, UT United States of America Utah Bad Oldesloe, Germany Germany Schleswig-Holstein Princeton, New Jersey, USA United States of America New Jersey lorient, france France Bretagne American Fork, Utah United States of America Utah Saint-Basile-le-Grand, Québec, Canada Canada Québec Apple Valley,MN United States of America Minnesota Montabaur, Germany Germany Rheinland-Pfalz Slough United Kingdom England Darlington, England United Kingdom England Leusden, The Netherlands Netherlands Utrecht Benesov Czechia Střední Čechy Olympia, WA United States of America Washington Wilmington United States of America Delaware Russia, Snezhinsk Russian Federation Челябинская область 38547 Calberlah Germany Niedersachsen Johnston, RI United States of America Rhode Island Gaithersburg, MD United States of America Maryland Redondo Beach, CA, USA United States of America California Luserna San Giovanni (TO), Italy Italy Piemonte Sammamish, WA USA United States of America Washington Redmond WA, USA United States of America Washington Alpharetta, GA United States of America Georgia Gibraltar Gibraltar Gibraltar Steamboat Springs, Colorado United States of America Colorado Chur, Switzerland Switzerland Graubünden/Grigioni/Grischun Randolph, NJ United States of America New Jersey Continued on next page

53 Table A18 – Continued from previous page Location string Geocoded country Geocoded state Aberystwyth United Kingdom Cymru / Wales Saint Augustine, FL, USA United States of America Florida France, Pau France Nouvelle-Aquitaine Burbank, CA United States of America California Melbourne Australia Australia Victoria Redmond, USA United States of America Washington Saint Augustine, FL United States of America Florida Foster City, CA United States of America California Split, Croatia Croatia — Glen Burnie, MD United States of America Maryland Heemskerk, Netherlands Netherlands Noord-Holland Cambridge, UK United Kingdom England Falconara Marittima AN - Italy Italy Marche Corvallis, Oregon, USA United States of America Oregon West Lafayette, Indiana United States of America Indiana Rome, NY United States of America New York Irpin, Kyiv, Ukraine Ukraine Київська область Maidenhead, UK United Kingdom England Mâcon, France France Bourgogne-Franche-Comté Orinda, California United States of America California Bethesda, MD United States of America Maryland Farnborough, Hampshire, United Kingdom United Kingdom England Berkeley, CA, USA United States of America California Redmond, WA, US United States of America Washington Goirle, The Netherlands Netherlands Noord-Brabant france,Toulon France Provence-Alpes-Côte d’Azur Kaysville, UT United States of America Utah Rockville, Maryland United States of America Maryland Milton, MA United States of America Massachusetts Savignano sul Rubicone Italy Emilia-Romagna Hatherleigh, Devon, UK United Kingdom England

54 Table A19—Random sample of 100, confidence=5 (96% accuracy)

Location string Geocoded country Geocoded state Los Alamos, NM United States of America New Mexico Saint-Quentin, France France Hauts-de-France Mariehamn, Åland Finland — Cambridge MA United States of America Massachusetts Shibuya-ku, Tokyo Japan — Victoria, British Columbia, Canada Canada British Columbia Charlottesville, VA United States of America Virginia Not San Francisco France Nouvelle-Aquitaine Aylesbury, UK United Kingdom of Great Britain and Northern Ireland England Jerseyville, IL. United States of America Illinois Commerce United States of America California Zaandam Netherlands Noord-Holland Forest Grove Oregon United States of America Oregon Port Washington, WI United States of America Wisconsin Uhldingen, Germany Germany Baden-Württemberg The Netherlands, Delft. Netherlands Zuid-Holland Silla Spain Comunitat Valenciana Nelsonville, OH, USA United States of America Ohio Brookline, MA, USA United States of America Massachusetts Beverly Hills, California United States of America California Granollers, Barcelona Spain Catalunya Feurs France Auvergne-Rhône-Alpes Brighton, England United Kingdom of Great Britain and Northern Ireland England Fuengirola, Málaga, Spain Spain Andalucía Kockengen, The Netherlands Netherlands Utrecht Los Altos Hills, CA United States of America California Ferndale, WA, USA United States of America Washington Grenoble, Isère, France France Auvergne-Rhône-Alpes Davenport, FL United States of America Florida New Westminster, BC, Canada Canada British Columbia Manchester,CT United States of America Connecticut Mataró, Catalonia Spain Catalunya Kailua, Hawaii United States of America Hawaii Victoria, Canada Canada British Columbia Aberdeen, MD United States of America Maryland Sant Fruitós de Bages (Barcelona) Spain Catalunya Louisville, CO United States of America Colorado Williamsburg, VA United States of America Virginia Margate United Kingdom of Great Britain and Northern Ireland England Amagansett, NY United States of America New York France - Arzon France Bretagne Grenoble France France Auvergne-Rhône-Alpes Merelbeke, Belgium Belgium Vlaanderen Schoonebeek Netherlands Drenthe Clemson, SC, USA United States of America South Carolina Marcq-en-Barœul, France France Hauts-de-France Flehingen, Germany Germany Baden-Württemberg San Carlos, California, USA United States of America California Teltow, Germany Germany Brandenburg Savenay, France France Pays de la Loire Taos, NM United States of America New Mexico Clemson, South Carolina United States of America South Carolina France, Grenoble France Auvergne-Rhône-Alpes Veenendaal, The Netherlands Netherlands Utrecht Basel - Switzerland Switzerland Basel-Stadt Moab, Utah United States of America Utah Lone Tree, CO United States of America Colorado Tourcoing, France France Hauts-de-France Grenoble, FRANCE France Auvergne-Rhône-Alpes Scotts Valley, CA United States of America California Victoria BC Canada British Columbia Grenoble, France France Auvergne-Rhône-Alpes Grenoble - FR France Auvergne-Rhône-Alpes Grenoble France Auvergne-Rhône-Alpes Cambridge, USA United States of America Massachusetts Mt. Pleasant, MI United States of America Michigan L’ile d’Elle France Pays de la Loire New Westminster Canada British Columbia Maarssen, The Netherlands Netherlands Utrecht Continued on next page

55 Table A19 – Continued from previous page Location string Geocoded country Geocoded state San Carlos, CA United States of America California Covington, WA United States of America Washington Schiedam, The Netherlands Netherlands Zuid-Holland Medford, NY United States of America New York San Lorenzo- Santa Fe- Argentina Argentina Santa Fe Malabar, FL United States of America Florida Geneve, Switzerland Switzerland Genève Salisbury, Wiltshire United Kingdom of Great Britain and Northern Ireland England Saint Priest sous Aixe (Limousin - France) France Nouvelle-Aquitaine Netherlands - Heiloo Netherlands Noord-Holland Delft, The Netherlands Netherlands Zuid-Holland Borlänge Sweden Dalarnas län Done Indonesia Nusa Tenggara Timur Bilthoven Netherlands Utrecht San Bruno, CA United States of America California Caen, France France Normandie Kailua, HI US United States of America Hawaii Woodstock, NY United States of America New York Albany, California United States of America California Innopolis, Russia. Russian Federation Татарстан eu France Normandie Alliance, Ohio United States of America Ohio Merelbeke, Belgium. Belgium Vlaanderen המרכז מחוז Modiin, Israel Israel Makati, Philippines Philippines — Altenholz, Germany Germany Schleswig-Holstein Santiago, Chile Chile Región Metropolitana de Santiago Bilthoven, Utrecht, the Netherlands Netherlands Utrecht Mataró Spain Catalunya Valkenburg, The Netherlands Netherlands Limburg Cambridge, Massachusetts United States of America Massachusetts

56 Table A20—Random sample of 100, confidence=6 (92% accuracy) Location string Geocoded country Geocoded state Chernogolovka, Russia Russian Federation Московская область valentine France Occitanie Barr, Ayrshire, Scotland United Kingdom Scotland Roseville, CA Canada Ontario Margretetorp Sweden Skåne län UK / Canada United Kingdom England Flax Bourton, Bristol, UK United Kingdom England Talence, France France Nouvelle-Aquitaine Melville, WA, Australia Australia Western Australia Phoenixville, PA United States of America Pennsylvania Sandpoint, Idaho United States of America Idaho Vienna, VA United States of America Virginia Danville, PA United States of America Pennsylvania Kula, Hawaii United States of America Hawaii Hever (Belgium) Belgium Vlaanderen Cricklewood, London, UK United Kingdom England New Lebanon, NY United States of America New York St. John’s, NL Netherlands Caribisch Nederland Casoria (Na) Italy Campania No simple highway France Pays de la Loire Heemstede, Netherlands Netherlands Noord-Holland BHM United States of America Alabama Miami Lakes, FL United States of America Florida nyon, switzerland Switzerland Vaud Blanc Mesnil, France France Île-de-France CA :: NY :: […China] United States of America New York Houston, TX & Germany United States of America Texas chuo-ku, Japan Japan — Boston / New York United States of America New York Lilburn, GA United States of America Georgia Wartenberg, Germany Germany — Sevenoaks Weald, Kent United Kingdom England Mohali, India India Punjab Vélizy, France France Île-de-France Greenbelt MD United States of America Maryland Lansdale, PA United States of America Pennsylvania University Park, Pennsylvania United States of America Pennsylvania Felton, CA Canada Ontario Smolenice Slovakia Trnavský kraj Snohomish WA United States of America Washington San Pedro, CA United States of America California Irvington, NY United States of America New York .Netland Norway — Louvain-La-Neuve Valley Belgium Wallonie Tassin-la-Demi-Lune - France France Auvergne-Rhône-Alpes RDU United States of America North Carolina Pully - Switzerland Switzerland Vaud Ithaca, NY and New York, NY United States of America New York the yay Lao People’s Democratic Republic — Chengdu, Sichuan Province, China. China 四川省 Muri bei Bern, BE, Switzerland Switzerland Bern/Berne Fairfax Va United States of America Virginia Embrach, Switzerland Switzerland Zürich Pontoise (France) France Île-de-France HERE Bosnia and Herzegovina Federacija Bosne i Hercegovine Hebron, KY United States of America Kentucky San Diego, U.S. Venezuela (Bolivarian Republic of) Táchira Lewes, UK United Kingdom England Louvain-la-Neuve Belgium Wallonie Lopătari, Romania Romania — Wals, Salzburg, Austria Austria Salzburg Wasserbillig, Luxembourg Luxembourg — Argonne, IL, US United States of America Wisconsin Texas Tech University United States of America Texas The University of Iowa United States of America Iowa North Carolina, Texas United States of America North Carolina Continued on next page

57 Table A20 – Continued from previous page Location string Geocoded country Geocoded state Oak Cliff, TX United States of America Texas Smithfield, Utah, USA United States of America Utah Yrisarri, NM United States of America New Mexico Cádiz Spain Andalucía Graton, CA United States of America California State College, PA United States of America Pennsylvania Asnieres-sur-Seine, France France Île-de-France 30% of the web Ethiopia Oromia Guangdong Province, China China 广西壮族自治区 Orsay France Île-de-France Winfield, IL United States of America Illinois Saratoga Springs, Utah United States of America Utah College Place, WA, USA United States of America Washington Brunswick, MD United States of America Maryland Iver Heath United Kingdom England Fairfax Station, VA United States of America Virginia Tuxedo Park, NY United States of America New York Bampton, Oxfordshire, UK United Kingdom England Reach United Kingdom England 四川成都 China 四川省 Europe, Potsdam Germany Schleswig-Holstein Denderleeuw, Belgium Belgium Vlaanderen Racour Belgium Wallonie Yangling, China China 宁夏回族自治区 Morristown, NJ United States of America New Jersey Hanover, Maryland United States of America Maryland Creil, France France Hauts-de-France Hawthorne, NJ United States of America New Jersey Gümligen Switzerland Bern/Berne Gorssel, Gelderland, The Netherlands Netherlands Gelderland Rocky River, Ohio United States of America Ohio Kreuzberg, Berlin, Germany Germany — Nyon, Switzerland Switzerland Vaud Berlin, NY United States of America New York

58 Table A21—Random sample of 100, confidence=7 (82% accuracy)

Location string Geocoded country Geocoded state Akihabara, Tokyo Japan — shaibu China 广东省 Kremlin-Bicêtre, France France Île-de-France Aichi, Japan Japan — 19 Countries Saudi Arabia — National University of Singapore Singapore — Falls Church VA United States of America Virginia Oakdale, CA Canada Ontario הצפון מחוז Israel, Afula Israel Caltech, Pasadena, CA United States of America California Rokko, Kobe, JAPAN Japan — Bresso, Milano - Italy Italy Lombardia Skipton, North Yorkshire United Kingdom England Asbury Park, NJ United States of America New Jersey Jersey Shore United States of America Pennsylvania Wilkinsburg, PA United States of America Pennsylvania Florence, MA USA United States of America Massachusetts Villetaneuse, France France Île-de-France Appalachian State University United States of America North Carolina 仙桃. 湖北 Japan — The milky way Seychelles — tero Norway — Sibuya, Tokyo Japan — Galt’s Gulch United States of America Utah University of Canterbury, Christchurch, New Zealand New Zealand Canterbury SZ China China 广东省 Mvd Uruguay Canelones West Grove, PA, USA United States of America Pennsylvania Bellport, NY United States of America New York Shinjuku, Tokyo Japan — Milky Way Seychelles — Otava, Mikkeli, Finland Finland — Dunston, Staffordshire United Kingdom England Windber, PA, USA United States of America Pennsylvania Oberentfelden / Switzerland Switzerland Aargau void France Grand Est Viroflay France France Île-de-France Notre Dame, IN United States of America Indiana Laporte, Minnesota, USA United States of America Minnesota UCSB United States of America California Towaco, NJ United States of America New Jersey Chicagoland, IL United States of America Illinois Greenfield, IA United States of America Iowa Peking University, Beijing, China China 北京市 University of Virginia United States of America Virginia University of Waterloo, Waterloo ON, Canada Canada Ontario Broek op Langedijk, The Netherlands Netherlands Noord-Holland Larkspur, CA Canada Alberta Rhineland United States of America Missouri Northbrook, IL United States of America Ohio Interstellar United States of America California Ebisu, Tokyo, Japan Japan — Deuil la barre, France France Île-de-France Philadelphia, NY United States of America New York Taplow, UK United Kingdom England North Germany Germany Bayern Harvard University, Cambridge, MA, USA United States of America Massachusetts milky way Seychelles — Sliema, Malta Malta Ċentrali Ås, Krokom, Sweden Sweden Jämtlands län CWRU, Cleveland, OH United States of America Ohio New Paltz, NY United States of America New York North Newton, KS United States of America Kansas Arakawa, Tokyo, Japan Japan — Pleasant Hill, CA Canada — General Fernandez Oro, Rio Negro, Argentina Argentina Río Negro Woodbridge VA Australia Western Australia Kennett Square, PA, USA United States of America Pennsylvania Burnie, Tasmania, Australia Australia Tasmania Continued on next page

59 Table A21 – Continued from previous page Location string Geocoded country Geocoded state Washington University in St Louis United States of America Missouri Berkley, CA United States of America Iowa Null island Germany Thüringen PID 0 France Centre-Val de Loire 52°51 N 13°373 E Poland województwo kujawsko-pomorskie Åre Sweden Jämtlands län Genval, Belgium Belgium Wallonie CMU, Pittsburgh, PA United States of America Pennsylvania Kensington, MD United States of America Maryland Økern, Oslo Norway — Saint Ouen France Hauts-de-France moravia United States of America Iowa Earth. United States of America Texas University of California, Irvine United States of America California University of Canterbury, New Zealand New Zealand Canterbury Steinhausen, Switzerland Switzerland Zug Amoy Fujian China China 福建省 SJO, Costa Rica Costa Rica Provincia Alajuela UTC -5 United States of America California Capellades, Catalunya Spain Catalunya Roxborough, CO United States of America Pennsylvania Bø Telemark, Norway Norway — Florida State University United States of America Florida Mountainview, CA Canada Alberta Bliżyn, Poland Poland województwo świętokrzyskie Wuhan University, Hubei, China China 湖北省 Black Rock City United States of America Nevada Nay Beijing China 北京市 Union City, CA 94587 United States of America California All around you China 浙江省 Brighton, CO United States of America Colorado

60 Table A22—Random sample of 100, confidence=8 (64% accuracy)

Location string Geocoded country Geocoded state Downey, CA Canada British Columbia University of Minnesota Morris United States of America Minnesota home Germany Nordrhein-Westfalen Nomad United States of America New York 1108 Western Avenue, Brattleboro, VT 05301 United States of America Vermont Near the edge of the world… Australia Western Australia 127.88.88.88 Philippines — Eastern Europe Poland województwo śląskie Development Heaven United States of America Washington Moon of Endor Australia Western Australia Pacific University, Forest Grove OR United States of America Oregon $HOME, Germany Germany Nordrhein-Westfalen The multiverse United Kingdom Scotland Lynbrook High School United States of America California /home Germany Nordrhein-Westfalen Potsdam (Berlin) Germany Schleswig-Holstein Slavyansk, Ukraine Ukraine Донецька область Southern Maine United States of America Maine Politechnika Wrocławska Poland województwo dolnośląskie École de technologie supérieure Canada Québec Everywhere :) Romania — Zürich & Winterthur, Switzerland Switzerland Zürich 百度科技园 2 号楼 China 北京市 HCMC, VN United States of America Minnesota Tricity Poland Poland województwo pomorskie The Dark Side of the Moon United States of America West Virginia הצפון מחוז Hararit, Israel Israel Western Massachusetts, USA United States of America Massachusetts Mountain View High School, Vancouver, WA United States of America Washington University College London United Kingdom England Deakin University Australia Victoria 50.758977, 6.082807 Germany Nordrhein-Westfalen Paris & Saclay France Île-de-France Москва, НИЯУ МИФИ Russian Federation Москва The Middle of Nowhere Canada British Columbia Sol III Chile Región de Atacama Mars; 火星 Russian Federation Московская область Terra / Earth Italy — Bangalore/Pune India Karnataka 198.41.0.4 Yemen — B.C. Canada Canada Ontario Paris Area Venezuela (Bolivarian Republic of) Miranda the Universe Denmark Region Syddanmark המרכז מחוז Canada/Israel Israel St. Petersburg state university, Russia Russian Federation Санкт-Петербург Northern Idaho United States of America Michigan UNR Argentina Santa Fe Majaka 26-211, 11411 Tallinn Estonia — Tatooine United States of America Vermont University of Auckland New Zealand — -95.3m France Hauts-de-France Bengaluru, Tamil Nadu India Tamil Nadu Imperial College London, United Kingdom United Kingdom England University of Science and Technology of China China 安徽省 University of Auckland, New Zealand New Zealand — 54.706901, 20.4981673 Russian Federation Калининградская область University of Auckland, Auckland, New Zealand New Zealand — Nanterre (Paris, France) France Île-de-France West Visayas State University La Paz, Iloilo City, Philippines Philippines — Greater Philadelphia Area, PA USA United States of America Pennsylvania Mérida, Yuc., Mex. Mexico Yucatán Greater Philadelphia Area, PA United States of America Pennsylvania Home Germany Nordrhein-Westfalen Universidad de Jaén Spain Andalucía Lakewood, Colorado United States of America Colorado Hubei.Wuhan.China China 湖北省 Lakewood, Colorado, USA United States of America Colorado Chinese Taipei Taiwan, Province of China 臺北市 Somewhere, Utah United States of America Utah Continued on next page

61 Table A22 – Continued from previous page Location string Geocoded country Geocoded state Everywhere. Romania — The Upside-Down Canada Saskatchewan In the middle of nowhere Canada British Columbia UCL United Kingdom England Monument, Colorado United States of America Colorado The clouds Thailand จังหวัดเพชรบุรี Half Moon Bay, CA Canada Alberta Queen Mary University of London United Kingdom England All over the US & Canada Spain Andalucía philly United States of America Pennsylvania SF, Paris Argentina Santa Fe Vadodara (Baroda), India India Gujarat 1200 Park Avenue Emeryville CA 94608 United States of America California Westeros Germany Brandenburg Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan Japan — Germany, Lusatia Germany Sachsen Dagobah United States of America Oregon Now-here United States of America Pennsylvania המרכז מחוז Rishon LeTzion, Israel Israel Brno, Moravia, Czech Republic Czechia Moravskoslezsko Greater Philadelphia Area, USA United States of America Pennsylvania Vienna / Rome France Nouvelle-Aquitaine Imperial College London United Kingdom England Sandhurst, Berks. United States of America Pennsylvania Silesia/Poland Poland województwo dolnośląskie San Franscico Brazil Bahia HCMC United States of America Minnesota ucsf United States of America California Malaysia, Earth Malaysia — Everywhere! Romania — Chihuahua, Chih. México Mexico Chihuahua

62 Table A23—Random sample of 100, confidence=9 (72% accuracy)

Location string Geocoded country Geocoded state us-west-1 United States of America Illinois Brussels, EU Belgium Région de Bruxelles-Capitale - Brussels Hoofdstedelijk Gewest Shinjyuku, Tokyo, Japan Japan — Moscow/SPb, RU Russian Federation Санкт-Петербург UTT, Troyes, France France Grand Est Kondavil , Jaffna, Sri Lanka Sri Lanka — Sunny San Diego United States of America Texas Berkeley & SF United States of America California Málaga (Spain) Philippines Laguna Malibu, CA Canada Québec China/Asia Venezuela (Bolivarian Republic of) Bolívar ПМР Тирасполь (PMR Tiraspol) Moldova, Republic of Нистрения / Приднестровье / Придністров’я on the road I am Australia — IFCE - Campus Maracanau Brazil Ceará New Wesminster, BC United States of America Missouri The High Seas United States of America Texas 19700 Helix Drive, Ashburn, VA 20147 United States of America Virginia Madrid | Jaén, Spain Spain Andalucía 深圳 ShenZhen China 广东省 Psalm 91 Philippines — Erie, CO United States of America Colorado Austin and Houston, Texas United States of America Texas TBD Falkland Islands (Malvinas) — Victoria Junior College Singapore — Jackson Wy United Kingdom England Wellcome Sanger Institute United Kingdom England 大都会 China 江西省 Santa Monica, CA Canada Québec Vikingskipet, Hamar, Norway Norway — 2788 San Tomas Expressway, Santa Clara, CA, 95051 United States of America California Rambouillet / Versailles / Paris / Tokyo France Île-de-France Bay Area | Houston TX United States of America Texas Home, United Kingdom United Kingdom Scotland Babylon, Long Island Iraq Herts, UK United Kingdom England github.com Brazil Rio de Janeiro Shanghai, Asia China 上海市 Barcelona (UPC) Spain Catalunya R.Korea suwon Korea, Republic of — Córdoba - Spain Philippines Laguna 2, Toegye-ro 36-gil, Jung-gu, Seoul, Republic of Korea Korea, Republic of — UC Santa Cruz Argentina Chaco jiangsu changzhou china China 江苏省 Paris/Prague France Île-de-France San Mateo, CA and Buenos Aires, Argentina Argentina Buenos Aires Auburn, Alabama United States of America Alabama Abuja/Lagos, Nigeria Nigeria Lagos All around the world. Canada British Columbia The (Middle) Earth United States of America California Goiânia - Porangatu - GO - Brazil Brazil Goiás Chicago area Philippines Rizal Naarm India Telangana Belem, Amazonia, Brazil Brazil Goiás Chicago Area Philippines Rizal Russian, Saint-Petersburg Russian Federation Санкт-Петербург Remote Ok United States of America Oklahoma The Wandering Sea United States of America Florida University of Luxembourg Luxembourg — McEnery Convention Center United States of America California San Francisco/Munich Chile Región de Arica y Parinacota 128 avenue du Maréchal De Lattre de France Nouvelle-Aquitaine Tassigny, 87000 Limoges, France Middle Earth United States of America California Metro Detroit, Michigan United States of America Michigan 41°52’57.0”N 87°37’18.5”W United States of America Illinois Washington D.C Metro United States of America District of Columbia Vestlandet, Norway Norway — Continued on next page

63 Table A23 – Continued from previous page Location string Geocoded country Geocoded state Chicago & SF United States of America California St. Thomas, VI Philippines — Europe, Germany Germany Schleswig-Holstein TEDA, Tianjin, China China 天津市 Paris, Nice France Provence-Alpes-Côte d’Azur IIIT Bangalore India Karnataka Metro-Detroit/Ann Arbor United States of America Michigan Auburn, AL USA United States of America Alabama No.6 Kexueyuan South Road Zhongguancun, China 北京市 Haidian District Beijing, China Germany, Europe Germany Schleswig-Holstein rhode island/florida United States of America Florida Glasgow / New Eden United Kingdom Scotland Metro Washington D.C. United States of America District of Columbia China.CS China 福建省 DMC United States of America Pennsylvania CS, China China 福建省 Chinese Beijing China 北京市 Up in the air Malaysia Pulau Pinang The British Museum United Kingdom England Paris - La Défense / France France Île-de-France Ottawa & Waterloo Canada Ontario Ottawa, ON and Waterloo, ON Canada Ontario 1 Cyclotron Rd, Berkeley CA 94720 United States of America California Central Coast NSW, Australia Australia — Arvada, Colorado, USA United States of America Colorado Sydney, Bronte Beach Australia — University of California, Davis United States of America California Dubai/Novi Sad Ukraine Львівська область Russia, KHMAO Russian Federation Ханты-Мансийский автономный округ —Югра East Bay, California, USA United States of America California france, le thor vaucluse France Provence-Alpes-Côte d’Azur Moscow Region Philippines — Auburn Alabama United States of America Alabama León Guanajuato, México Mexico San Luis Potosí

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